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Socially Aware Natural Language Processing With Commonsense Reasoning And Fairness In Intelligent Systems, Sirwe Saeedi
Socially Aware Natural Language Processing With Commonsense Reasoning And Fairness In Intelligent Systems, Sirwe Saeedi
Dissertations
Although Artificial Intelligence (AI) promises to deliver ever more user-friendly consumer applications, recent mishaps involving fake information and biased treatment serve as vivid reminders of the pitfalls of AI. AI can harbor latent biases and flaws that can cause harm in diverse and unexpected ways. It is crucial to understand the reasons for, mechanisms behind, and circumstances under which AI can fail. For instance, a lack of commonsense reasoning can lead to biased or unfair decisions made by Machine Learning (ML) systems. For example, if an ML system is trained on data that is biased or unrepresentative of the real …
Cross Language Information Transfer Between Modern Standard Arabic And Its Dialects – A Framework For Automatic Speech Recognition System Language Model, Tiba Zaki Abdulhameed
Cross Language Information Transfer Between Modern Standard Arabic And Its Dialects – A Framework For Automatic Speech Recognition System Language Model, Tiba Zaki Abdulhameed
Dissertations
Significant advances have been made with Modern Standard Arabic (MSA) Automatic Speech Recognition (ASR) applications. Yet, dialectal conversation ASR is still trailing behind due to limited language resources. As is the case in most cultures, the formal Modern Standard Arabic language is not used in daily life. Instead, varieties of regional dialects are spoken, which creates a dire need to address dialect ASR systems. Processing MSA language naturally poses considerable challenges that are passed on to the processing of its derived dialects. In dialects, many words have gradually morphed from MSA pronunciations and at many times have different usages. Also, …
Social Media Sentiment Analysis With A Deep Neural Network: An Enhanced Approach Using User Behavioral Information, Ahmed Sulaiman M. Alharbi
Social Media Sentiment Analysis With A Deep Neural Network: An Enhanced Approach Using User Behavioral Information, Ahmed Sulaiman M. Alharbi
Dissertations
Sentiment analysis on social media such as Twitter has become a very important and challenging task. Due to the characteristics of such data (including tweet length, spelling errors, abbreviations, and special characters), the sentiment analysis task in such an environment requires a non-traditional approach. Moreover, social media sentiment analysis constitutes a fundamental problem with many interesting applications, such as for Business Intelligence, Medical Monitoring, and National Security. Most current social media sentiment classification methods judge the sentiment polarity primarily according to textual content and neglect other information on these platforms. In this research, we propose deep learning based frameworks that …
Exploring The Dynamics Of Scientific Research, Shilpa Lakhanpal
Exploring The Dynamics Of Scientific Research, Shilpa Lakhanpal
Dissertations
Scientific research papers present the research endeavors of numerous scientists around the world, and are documented across multitudes of technical conference proceedings, and other such publications. Given the plethora of such research data, if we could automate the extraction of key interesting areas of research, and provide access to this new information, it would make literature searches incredibly easier for researchers. This in turn could be very useful for them in furthering their research agenda. With this goal in mind, we have endeavored to provide such solutions through our research. Specifically, the focus of our research is to design, analyze …